chore(ui): regenerate dashboard API types for the tool turns flag description

ui/litellm-dashboard/src/lib/http/schema.d.ts

@@ -42470,7 +42470,7 @@ export interface components {
             classifier_context_include_assistant_turns: boolean;
             /**
              * Classifier Context Include Tool Turns
-             * @description Send the tool calls and tool results that followed the current ask to the classifier as the work done on it so far, so an agent loop's continuation turn is classified on what its tools turned up rather than on the ask alone: 'What is in TASK.md?' stays SIMPLE until the file it reads describes a complex task, and the turns after that classify as that task. With classification_mode='every_request' every turn of the loop is classified this way. With classification_mode='user_turn' the tier pinned for the ask is a floor for its tool turns: each one is classified, and only a higher tier moves the session up and replaces the pin, so a loop never drops back mid-task, at the cost of a classifier call per tool turn. Under heuristic_first and hybrid a turn with tool traffic always goes to the classifier model, since the local scorer reads only the ask. The block is bounded on its own by classifier_context_budget_chars and classifier_context_per_turn_chars, newest first, but not by classifier_context_window_size, since one ask can run dozens of tool calls; setting the window size to 0 still turns all context off. Tool output such as file contents is sent to the classifier model, which may be a different deployment or provider than the routed completion model. Off by default because enabling it shifts tier decisions, and therefore spend, for an already-deployed router. Requires classifier_type llm, oss_classifier, heuristic_first, or hybrid, the ones that send the conversation to a classifier model, and cannot be combined with session_affinity, which replays its pin without classifying.
+             * @description Send the tool calls and tool results that followed the current ask to the classifier as the work done on it so far, so an agent loop's continuation turn is classified on what its tools turned up rather than on the ask alone: 'What is in TASK.md?' stays SIMPLE until the file it reads describes a complex task, and the turns after that classify as that task. With classification_mode='every_request' every turn of the loop is classified this way. With classification_mode='user_turn' the tier pinned for the ask is a floor for its tool turns: each one is classified, and only a higher tier moves the session up and replaces the pin, so a loop never drops back mid-task, at the cost of a classifier call per tool turn, which the turn waits on, up to the classifier timeout, before it routes. A tool turn whose classifier call fails keeps the held tier, and with the circuit breaker on it opens a breaker of its own, so later tool turns replay the pin at once while new asks keep classifying. Under heuristic_first and hybrid a turn with tool traffic always goes to the classifier model, since the local scorer reads only the ask. The block is bounded on its own by classifier_context_budget_chars and classifier_context_per_turn_chars, newest first, and once a loop overflows that budget each entry is cut to a quarter of it, so one large file read cannot push out the rest. It is not bounded by classifier_context_window_size, since one ask can run dozens of tool calls; setting the window size to 0 still turns all context off. Tool output such as file contents is sent to the classifier model, which may be a different deployment or provider than the routed completion model. Off by default because enabling it shifts tier decisions, and therefore spend, for an already-deployed router. Requires classifier_type llm, oss_classifier, heuristic_first, or hybrid, the ones that send the conversation to a classifier model, and cannot be combined with session_affinity, which replays its pin without classifying.
              * @default false
              */
             classifier_context_include_tool_turns: boolean;